Volume 11 Supplement 1

Beyond the Genome: The true gene count, human evolution and disease genomics

Open Access

Evolution of haplotypes at CCL3L1/CCL4L1

  • Somwang Janyakhantikul1,
  • Danielle Carpenter1 and
  • John AL Armour1
Genome Biology201011(Suppl 1):P20

https://doi.org/10.1186/gb-2010-11-s1-p20

Published: 11 October 2010

Background

CCL3L1 and CCL4L1 are chemokine genes, located on chromosome 17q12 (Figure 1). They are copy number variable genes that share 95% sequence identity with their non-copy number variable paralogues CCL3 and CCL4 [1]. The copy number (CN) of these genes varies between populations [2] and has been shown to be associated with phenotypes, such as susceptibility to HIV infection [2] and SLE [3]. A CCL3L1 pseudogene, also known as CCL3L2, is present in the CCL3L1 region. This pseudogene has sequences similar to CCL3L1 gene, but lacks exon 1 of CCL3L11. As a result, its presence might affect copy number (CN) measurement and subsequent interpretations in association studies between CCL3L1 CN and diseases [4]. The copy number of CCL3L1/CCL4L1 was measured using paralogue ratio test (PRT) in 270 HapMap samples 192 UK samples and 157 Basques samples [5]. Firstly, we examined the association between the presence of the CCL3L1 pseudogene and CCL3L1 CN in the UK samples and HapMap samples by PCR. The pseudogene was found in 52 out of 192 (27.08%) of UK samples. The presence of this pseudogene is strongly associated with higher copy number of CCL3L1/CCL4L1 (P<1 ×10-10) (Figure 2). The presence of the pseudogene was tested in all HapMap populations (Table 1). SNP genotyping and CCL3 microsatellite assays were then carried out to define a set of flanking markers that may predict CCL3L1/CCL4L1 CN in UK and Basque samples. The best combination of 2 flanking SNPs, rs16972085 and rs8064426, can be used - to predict the CCL3L1/CCL4L1 CN in UK and Basque samples with only 70% accuracy. Although the CCL3 microsatellite alleles are not associated with CCL3L1/CCL4L1 copy number, there is extensive allelic diversity in the microsatellite. Finally, to improve the accuracy of CCL3L1/CCL4L1 CN prediction, the CCL3L1/CCL4L1 genes were sequenced in 90 CEU samples to identify sequence variants within the copy-variable genes themselves. Analysis of CCL3L1/CCL41 haplotypes in CEU samples is underway to provide information on evolution of the CCL3L1/CCL4L1 haplotypes and the relationship between these haplotypes, flanking SNPs and the presence of the CCL3L1 pseudogene.
Figure 1

Diagram of CCL3L1 and CCL4L1 at Chr.17q12 and the primers used in the CCL3L1 pseudogene assay (not to scale).

Figure 2

Relationship between presence of the pseudogene and CCL3L1/CCL4L1 copy number in 192 UK samples.

Table 1

Copy number of CCL3L1/CCL4L1 and presence of CCL3L1 pseudogene in HapMap populations.

Samples

Population

Number of samples

Range of CCL3L1/CCL4L1 CN

Mean CCL3L1/CCL4L1 CN

Frequency of CCL3L1 pseudogene positive (%)

Yoruba

African

90

2-10

5

58 (64.44%)

CHB-JPT

Asian

90

1-8

4

48 (53.33%)

CEU

European

90

0-3

2

17 (18.89%)

Conclusion

The CCL3L1 pseudogene and the combination of SNPs rs16972085 and rs8064426 are associated with the CCL3L1/CCL4L1 copy number, but the association is not absolute. However, data on evolution of CCL3L1/CCL4L1 haplotypes and the relationship between these haplotypes, flanking SNPs and the CCL3L1 pseudogene in CEU samples could provide variable insight to this region.

Authors’ Affiliations

(1)
Institute of Genetics, School of Biology, University of Nottingham

References

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Copyright

© Janyakhantikul et al; licensee BioMed Central Ltd. 2010

This article is published under license to BioMed Central Ltd.

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